[Offline & Private AI Systems]

Offline & private AI.
Under your control.

Private AI systems and computing infrastructure, from field devices to larger installations, with model deployment and defined offline operation.

Discuss a ProjectWhat We Build

[ Where This Fits ]

Built around the requirement.

When information needs to stay within your environment or work must continue without an external connection, the models, applications, and infrastructure need to work together. We design and supply the system around the workload, quality requirements, and budget, from a field device to dedicated workstations, servers, or a larger private installation.

  • Field teams using reference material or collecting information without dependable internet.
  • Organizations needing larger private models, internal applications, and controlled access to company information.
  • Dedicated devices with specific limits on power, memory, storage, or heat.

Field Deployment Brief

[ What We Build ]

The system, end to end.

[ 01 ]

Models and computing infrastructure

Select and evaluate models against representative tasks. Procure and assemble the workstations, servers, or device hardware the assignment requires, with memory, storage, power, and cooling planned around the workload.

[ 02 ]

Applications and controlled access

Build the user interface, model services, document retrieval, storage, and access controls. A system can use private models, approved model APIs, or both. Define where information can go and which functions remain available without an external service.

[ 03 ]

Updates and recovery

Package installation and model or document updates. Where connectivity returns periodically, define queued work, synchronization, conflict handling, and recovery after interruption.

[ Example System Design ]

A technical assistant for disconnected field work.

An example system design: a technician uses approved manuals and records site observations on a dedicated device. The essential workflow remains available while disconnected.

  1. [ 01 ]

    Local reference library

    Approved documents are prepared and versioned before installation.

  2. [ 02 ]

    On-device inference

    The application retrieves relevant passages and runs the selected model locally.

  3. [ 03 ]

    Operator review

    The user sees source references and confirms recorded work.

  4. [ 04 ]

    Controlled synchronization

    Approved updates and queued records transfer when a connection is available.

[ Acceptance ]

Agree what success means.

  • Complete the agreed local workflows with external network access disabled and verify the data boundaries for connected functions.
  • Measure answer quality, response time, capacity, and resource use on the target infrastructure.
  • Check missing-information behavior, restart, and interrupted synchronization.

[ Source & Handover ]

Ownership and continued development.

The agreed delivery includes commissioned application source, runtime and model configuration, installation instructions, evaluation cases, and maintenance documentation. Model and third-party licences are identified so your team understands what it can use and modify.

Project delivery and ownership

[ Project Questions ]

Before we begin.

Does private AI always mean fully offline?
No. A system can run on company-controlled servers, entirely on a device, or across both. Where the project permits it, approved model APIs can support selected workflows. We define the data boundary and the functions that must remain available without a connection.
Can you supply the hardware for a larger private installation?
Yes. Hardware procurement, workstation and server assembly, model deployment, and testing can be part of the commission. The workload, quality requirements, and budget determine the model and infrastructure.
Can this run on a phone or a small computer?
The workload determines that. A feasibility stage tests representative models and tasks on candidate hardware before the device specification is fixed.
Can the system use our own documents?
Yes. We can build a controlled document preparation and retrieval process, with access permissions, source references, and a way to update the local library.

[ Contact ]

Start with the requirement.

Tell us what the system needs to do, what data it will use, and which functions must work locally. Include the intended scale, available infrastructure, and project budget; we can develop the hardware specification as part of the assignment.

Discuss a Project contact@freelifeai.com